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- Course
Global greenhouse gas emissions are now at a record high, and the world’s scientific community agrees
that continued unabated release of greenhouse gases will have catastrophic consequences. Many efforts
to curb greenhouse gas emissions, both public and private, have been underway for decades, yet it is
now clear that collectively these efforts are failing, and that far more concerted efforts are necessary. In
December 2015, the world’s nations agreed in Paris to take actions to limit the future increase in global
temperatures well below to 2°C, while pursuing efforts to limit the temperature increase even further to
1.5°C. The importance of limiting global temperature increases to 1.5°C was highlighted by the IPCC SR15
report, which increased global urgency around this objective. Achieving this goal will require mitigation
of greenhouse gas emissions from all sectors, both public and private. Critical to any attempt to mitigate
greenhouse gas emissions is a clear, accurate understanding of the sources and levels of greenhouse gas
emissions. This course will address all facets of greenhouse gas emissions accounting and reporting and
will provide students with tangible skills needed to direct such efforts in the future.
Students in this course will gain hands-on experience designing and executing greenhouse gas emissions
inventories, employing all necessary skills including the identification of analysis boundaries, acquisition
of data, calculation of emissions levels, and reporting of results. In-class workshops and exercises will
complement papers and group assignments. A key component of this exercise will be critical evaluation
of both existing and emerging accounting and reporting protocols.
This course will introduce many of the challenges facing carbon accounting practitioners and will require
students to recommend solutions to these challenges derived through critical analysis. Classes will
examine current examples of greenhouse gas reporting efforts and will allow students the opportunity to
recommend improved calculation and reporting methods.
Assignments will consist of readings and technical analysis projects. Students are expected to have basic
experience using Microsoft Excel and basic quantitative skills. However, full Excel proficiency is not
required.
- Topics on: Decarbonization, Reporting and Measurement
- Course
Cost-Benefit Analysis (CBA) is a policy assessment method that quantifies the value of policy consequences
(usually called impacts) in monetary terms to all members of society. The purpose of a CBA is to help effective
social decision making through efficient allocation of society’s resources when markets fail. When markets fail and
resources are used inefficiently, CBA can be used to clarify which of the potential alternative programs, policies or
projects (including the status quo) is the most efficient.
The course introduces practitioners of sustainability management & sustainability science to the techniques of
preparing a CBA, including microeconomic foundations, valuation methods, discounting, the impact of uncertainty
and optionality, and distributional consequences. The course provides a basic introduction to revealed preference,
contingent valuation and benefits transfer method of valuing environmental impacts.
The use and interpretation of CBA in specific cases is critically evaluated, with a detailed examination of alternative
approaches. Worked examples and case studies are integral to each topic. Although the techniques of CBA are
generally associated with social decision-making, we will examine case studies involving both social and private
decisions.
This course is both for those who want to perform CBA and those who want to know how to understand and
interpret it: in other words, the various clients of CBA. Students are assumed to have had no previous exposure to
economics. Students who have had an undergraduate course in intermediate microeconomics or taken Economics of
Sustainability Management will be adequately prepared to excel in the course. Those who have not had such
preparation will need to work hard to absorb the theoretical concepts along with the applications. However, it is not
uncommon for students with little economics preparation to excel in a course on CBA. In the absence of any
economics preparation, it is useful to have some mathematical fluency. If you are concerned about your level of
mathematics preparation, you are strongly encouraged to attend the Math Camp provided during the first few
weekends of the Fall semester or to go through the notes and exercises in the Foundations course site.
- Topics on: Economics
- Course
Data science is an exciting new field of applied research that takes advantage of the ever-growing volume of data
being collected to support decision-making in both the public and private sectors. Similar to traditional statistical
analysis, these new approaches have limits and issues that are important to understand before application to problem
solving. This is a full semester course taught in person. It aims to introduce the common methods used in data
science, best practices in data management, and the basic scripting skills required to start analyzing data in R and
Python. After introducing foundational scripting and data analysis methods, a case study approach will be used to
highlight both what can be accomplished with data analysis and the limits of the data and methods used. Lab
exercises will teach basic skills in scripting in Python and R and then move to a common approach for data analysis:
adapting existing scripts and software libraries to solve applied data problems.
The requirement to understand the interaction of social and natural systems requires data-driven policy decisions,
and the ongoing assessment of policies requires rigorous, reproducible assessments of effectiveness for promoting
sustainability. Both requirements can be met in part by data science approaches that are applicable to the natural and
social sciences and reproducible in academic and applied settings. Data science techniques have been developed to
derive insight from large volumes of available data that are often collected for purposes other than the interests of
the data scientist. This flexibility in approach means that the techniques used in data science are well adapted to
support gaining insights from data relevant for sustainability science. This course has been designed to introduce
these techniques in anticipation of increased use in promoting sustainability.
The course has no prerequisites; however, an understanding of statistics and probability will be very useful
background, and any previous programming or scripting skills will be applicable to the lab assignments. This course
satisfies the M.S. in Sustainability Management program’s Area 2: Quantitative Analysis requirement. The course
is open, space permitting, to cross-registrants from other fields and/or Columbia University programs.
- Topics on: Analytics, Data Science
- Course
Life Cycle Assessment (LCA), a methodology to assess the environmental impact of products, services, and
industrial processes, is an increasingly important tool in corporate sustainability management.
The course will provide continuous context regarding the need for environmental analysis of product design,
services, and industrial processes. LCA will be thoroughly explained and conducted, including both the advantages
and shortcomings. The course will humanize the environmental data through readings and discussion. Design
strategies will also be examined as a larger system context for which to conduct an LCA.
The course also covers the application of LCA metrics in a companies’ management and discusses the logical
weaknesses that make such an application difficult, including how these can be overcome. Product carbon
foot-printing (as one form of LCA) receives particular focus, owing to its widespread practical use in recent and
future sustainability management.
- Topics on: Impact, Reporting and Measurement
- Course
We begin by introducing the linkages between the environment and the economy. We discuss methods by which
aggregate resource allocation decisions occur in capitalist economies, with implications for social welfare and
economic efficiency. We briefly discuss the policy and welfare implications of perfectly competitive markets that
represent an idealized analytical benchmark. We then analyze markets where the benchmark assumptions do not
hold. We see how a laissez-faire approach leads to inefficient outcomes in the presence of “market failures” such as
monopoly power, externalities, and public goods.
We discuss the appropriateness of various public policy options (taxes, subsidies, regulations, public provision of
goods and services) to correct these failures. We examine practical steps in the implementation of these tools by
studying environmental valuation techniques and cost-benefit analysis. We examine “government failure” to
consider the limits of regulatory intervention arising from asymmetric information and the limitations of political
economy.
We then analyze more sophisticated regulatory approaches that consider information problems. We also study the
possibilities for sustainability that arise from corporate social responsibility. We examine basic techniques of
renewable and non-renewable resource management. We analyze the implications of risk management methods for
resource allocation.
- Topics on: Economics
- Course
The course provides an overview of the scenario analysis and climate risk modeling process for corporate issuers
and government entities. There is a brief introduction to the climate models utilized by the IPCC, both global and
regional. There is a description of the scenario generation and analysis process, with linkages to benchmark
scenarios outlined by international bodies. This is followed by a review of the linkages between climate models and
socio-economic variables in the form of integrated assessment models, Ricardian models and economic input-output
analysis. There is one module on the information systems needed to ensure good adaptation and a review of best
practices and guidelines for climate risk management strategies. Integrated examples of climate risk and
opportunities for specific issuers are discussed in the last 2 classes. The problem sets and exercises are designed to
provide practice in applying high-level guidelines and climate damage relationships to the strategies and operations
of specific countries, industries and companies.
- Topics on: Business, Governance, Reporting and Measurement
- Course
Modernizing energy systems is essential for achieving a sustainable future. In the 18th century, society’s dependence
on whale oil for lighting nearly drove whale populations to extinction—until the invention of kerosene provided a
cheaper, more efficient alternative. This historical shift illustrates how technological breakthroughs can
fundamentally resolve systemic crises. Today, fossil fuels present an even greater environmental and geopolitical
challenge. The solution lies in the electrification of energy consumption and the rapidly declining costs of renewable
energy. Although electricity currently accounts for about 20% of global final energy consumption, it is projected to
exceed 50% by mid-century. This transition—driven by renewables like solar and wind—demands a modernized
grid capable of reducing carbon emissions, meeting growing energy needs, and managing complex operational
dynamics.
The IES course dives into how intelligent energy systems can help solve some of the biggest challenges in today’s
clean energy transition. As we shift away from fossil fuels toward electricity powered by renewables like solar and
wind, the power grid must also evolve. Right now, electricity makes up just 20% of global energy use—but that
number is expected to rise to over 50% by mid-century. To keep up, we need smarter, more flexible grids that can
handle things like energy intermittency, curtailment, and growing demand. Technologies like Battery Energy Storage
Systems (BESS) and Artificial Intelligence (AI) are key to making this happen. In this course, you’ll learn how these
tools are already reshaping the energy industry—and gain the practical skills to be part of this transformation.
This elective course is designed for students in Columbia University’s Master of Science in Sustainability
Management program, particularly those interested in the intersection of renewable energy, technology, and
environmental stewardship. The program is dedicated to preparing professionals with the knowledge and tools to
develop and implement effective sustainability strategies. This course supports that mission by emphasizing
transformative technologies in grid modernization, highlighting the pivotal roles of AI and BESS.
- Topics on: Energy, Innovation, Technology
- Course
At the end of this course, students will be prepared to fully evaluate the technical and financial aspects of a solar
project. They will be equipped with skills allowing them to either develop or rigorously vet solar project proposals.
The course introduces and provides students with a holistic understanding of the end-to-end solar development
process. The course has two goals:
1. To provide students a deep understanding of the dozens of critical interrelated steps critical to developing a
successful operating solar project.
2. To equip the students with the tools and understanding of the skills necessary to develop a solar project
beginning with site selection encompassing the entire process to commissioning and operations.
- Topics on: Energy, Finance, Solar, Technology
- Course
This survey course examines a range of sustainable and impact investing fixed income and equity products
before transitioning to the asset owner perspective on sustainable and impact investing. Each class session
includes elements of financial analysis, financial structure, social or environmental impact, and policy and
regulatory context. Brief guest lectures, podcasts, and three experiential exercises bring these topics to life.
At the end of the course, each student will be able to (i) construct a diversified portfolio of impact
investments based on the range of products tackled in class, (ii) integrate ESG into debt and equity valuation,
(iii) develop an impact investing product that an asset manager or investment bank could launch, (iv) develop
an impact investing strategy for an asset owner, and (v) lead either side of the investor-corporate dialogue on
sustainability. The lectures are designed to prepare students for both the impact investing product
development exercise and the impact investing asset owner strategy exercise, and these two exercises are
designed to prepare students for impact investing leadership over the course of their careers.
As an early innovator in social finance, dating back 24 years, the instructor provides students with a practical
toolkit, honed by making mainstream financial institutions and products more beneficial to a broader range
of stakeholders and making specialist impact investment firms more relevant to and integrated with
mainstream markets.
The course has no prerequisites; however, an understanding of finance and completing the SUMA Foundations
Module will be useful background. Homework assignment 0 is a mandatory review of introductory finance.
This course satisfies the M.S. in Sustainability Management program’s Area 5: General and Financial
Management requirement.
- Topics on: Finance, Investing
- Course
The course provides a grounding in modern portfolio theory, the capital asset pricing model and the framework to
evaluate hypotheses and accepted techniques in sustainable investing. We examine the financial economics
foundations of modern portfolio theory and the standard factor-based return and risk attribution framework in order
to provide a context for responsible investment practices in the marketplace. It examines the relationship between
investment return expectations, economic growth and sustainability initiatives.
- Topics on: Business, Economics, Finance, Investing
- Course
Entrepreneurship is all the rage in conversations on Wall Street and Main Street. Everyone and their neighbor seems to want the
glitz and glamour of starting a successful company and being their own boss, but few take the plunge because of the inherent risks
and tiresome challenges of developing an early-stage company. This course applies entrepreneurial thinking to different business
models as seen through a social, environmental, and economic sustainability perspective. The course will explore the relationship
between society’s need for business development and costs to the environment. You will study ways in which sustainable
entrepreneurship can significantly diminish dependency on fossil fuels and toxic substances. The course will challenge you to
conceive and pitch a sustainable entrepreneurial or intrapreneurial business concept. Guest lectures, readings, case studies,
activities, and group work will support the development of your entrepreneurial venture.
This course is distinctive from others at Columbia in several ways. This course puts sustainability concepts to work by inspiring
students to think about value creation through the lens of ecological and social stewardship; then to test market their ideas,
evaluate the business landscape, and create a thoughtful business plan and execution strategy. The class is appropriate for those
with an interest in the unique challenges of starting a social good or clean technology company.
This course requires business and technical proficiency gained in a competitive undergraduate program or commensurate
professional experience.
This is an elective course and is approved to satisfy “Area 5 – General and Financial Management” requirement for the M.S. in
Sustainability Management curriculum.
- Topics on: Business
- Course
Throughout history maps have reflected and shaped map makers’ worldviews, displayed, conveyed and visualized
spatial information. Maps summarize data trends and patterns in the human, social and natural sciences. Much of the
data we use daily (from google maps entries to tabular data to texts and speeches) are explicitly or implicitly geo-
referenced. The ability to leverage these spatial references allows us to identify and study patterns in the data.
Geographic Information Systems (GIS) are a set of modern tools to collect, store, analyze and display spatial
information. As part of this elective class, students receive a comprehensive introduction to GIS theory and software
through a mix of lectures, readings, focused discussions, hands-on exercises and a final project. Students are
exposed to the variety of spatial data and databases, gain knowledge of the principles behind raster- and
vector-based spatial analysis and learn basic cartographic principles for producing maps that effectively
communicate a message.
Students learn to use the software ArcGIS Pro and leverage web-based GIS tools such as ArcGIS Online and similar
tools to develop online interactive maps and graphics. Case studies examined in class will draw from a wide range
of GIS applications to assist in the design, implementation and evaluation of sustainable development projects and
programs.
This class is designed for students new to GIS and those who have had some experience. Students are welcome to
bring their own data for the final project or to discuss how GIS tools may be useful for data exploration and
research.
- Topics on: Analytics, Data Science, Geography
- Course
This course is designed to provide students with working knowledge on how to make successful investments in
sustainable companies and to prepare students to be conversationally literate in financial reporting. As you leave the
school and become leaders of organizations, financial literacy will be a skill set that will be vital to success no
matter what career path you go down. It starts with a strong foundation in accounting and corporate finance, then
moves on to ESG/Impact screening of potential investments, along with valuation techniques used to arrive at a
purchase price. It will explore financial models that can aggregate multiple variables used to drive investment
decisions.
- Topics on: Finance
- Course
The course introduces practitioners of sustainability management to the data analysis techniques and
statistical methods which are indispensable to their work. The class teaches how to build statistical
substantiation and to critically evaluate it in the context of sustainability problems. The statistics topics
and examples have been chosen for their special relevance to sustainability problems, including
applications in environmental monitoring, impact assessment, and econometric analyses of sustainable
development. Students are assumed to have had no previous exposure to statistics.
- Topics on: Analytics, Data Science, Reporting and Measurement
- Course
Over the past two decades, public and private institutions have set clear targets for environmental, economic, and
social performance and they are increasingly using analytical tools to assess problems and measure progress. The
advent of “Big Data” has accelerated this work – and opened up new possibilities and challenges. This course will
examine the use of data and metrics to shape and implement sustainability policies and programs and to assess and
communicate their outcomes.
The course will survey a range of real-world sustainability challenges and evaluate the choices confronting public
officials, private companies, NGO’s, advocates, and citizens – and the data that can be used to diagnose problems,
develop solutions, and measure success. Particular focus will be given to urban sustainability efforts and corporate
sustainability. We will explore how data can be used and misused in each of these domains. Throughout we will
emphasize the importance of context, comparability, and completeness of information.
Students will be required to critically evaluate what they read and hear. In addition, the course will give students an
opportunity to learn how to express their ideas verbally and in written form and conduct a critical analysis of how
environmental data is used to develop and implement public policy. Assignments will give students the opportunity
to use their technical and analytical skills while understanding the real-world applications that will be important to
their future work as planners, policymakers, advocates, architects, environmentalists, or other professions. The
course will feature guest lectures from speakers who are leaders in their fields. Lecture topics may be moved to
accommodate speaker travel and availability. Notice will be provided to students in advance of any schedule
changes.
- Topics on: Analytics, Data Science, Reporting and Measurement
- Course
The urgency to tackle sustainability-related global problems has revealed the growing need to create, maintain and
analyze data on environmental and social issues with robust methodologies. The availability of nascent sustainability
datasets and advanced data tools such as GIS, machine learning, and blockchain has expanded our capabilities for
quick and agile decision-making in the sustainability space. However, compared to real-time economic data, timely
and reliable environmental and social data are very much lacking.
Sustainability indicators are able to transform a vast amount of information about our complex environment into
concise, policy-applicable and manageable information. There is a very large universe of indicators to measure the
sustainability performance of an entity, but the critical question is what to use and how many indicators should be
evaluated. Sustainability indicators are either presented in a structured framework that can be used to isolate and
report on relevant indicators, or aggregated towards a composite index or score/rating.
The number of indicators used for assessing sustainability have proliferated, with hundreds of sustainability related
indices around the world, including the Ecological Footprint, the Human Development Index, green accounting,
Sustainable Development Goals, the Environmental Performance Index (EPI) co-developed by Columbia University
and Yale University, the Urban Sustainability Ranking System that I helped develop, and various carbon indices.
The course is divided into three sections. The first section will visit different definitions of sustainability to outline
the theoretical premises on which current data practices and policies are built, and then outline the most commonly
used frameworks and indices that are used to measure sustainability. The second section focuses on the construction
of sustainability indices or composite indicators, and outline the methods frequently used in constructing indices,
such as standardization, weighting, and aggregation, and analyze how sustainability frameworks can assist in the
selection of indicators, which is often the most important yet most inconsistent step in constructing an index. The
last section focuses on how composite sustainability indicators are used in practice. This section will discuss the
SDGs, urban sustainability indicators, environmental performances indices, the relationship between sustainability
and financial performance, the relationship between sustainability and business performance, how to use
sustainability data to make investment decisions with a case study on impact investment evaluation.
The course will highlight the strengths and limitations of data that contribute to the selection of proper indicators,
the methods for their normalization and aggregation into indices, and their use in the real world. For example,
students will learn how to use different datasets and calculation guidelines to assess cities’ environmental, and social
footprint. This will help students gain the knowledge of data sources, and process these data through suitable
methodologies to identify the sustainability-related risks and opportunities. Students will learn to critically assess
existing indicators and indices, focusing on data cleanliness and robustness, and to construct their own
index/rating/ranking for a thematic area and a region using the software they are most comfortable using (e.g.,
Excel, SPSS, Stata, R, Python, etc.).
- Topics on: Analytics, Data Science, Reporting and Measurement
- Course
The urgency to tackle sustainability-related global problems has revealed the growing need to create, maintain and
analyze data on environmental and social issues with robust methodologies. The availability of large datasets and
advanced data tools such as GIS, machine learning, and blockchain has expanded our capabilities for quick and agile
decision-making in the corporate and urban space. However, more data does not necessarily mean better solutions.
This course will explore the relationship between sustainability and data from corporate and urban perspectives,
focusing on how data is created, analyzed and used to make decisions. The course is divided into three sections. The
first section focuses on measuring sustainability and will start by visiting different definitions of sustainability to
outline the theoretical premises on which current data practices and policies are built. The second section focuses on
examples of sustainability/ESG data in corporate management through case studies such as Home Depot, Amazon,
Nestle and others. The last section focuses on disclosure and use of data by different stakeholders, with special
attention on data integrity, data contingencies and disclosure risks. This section will address developing trends in
voluntary and mandatory data disclosure frameworks.
The course will highlight the importance of actionable data, purpose-driven analysis and the selection of proper
indicators. Moreover, students will learn how to find and use different datasets and calculation guidelines to assess
corporations and cities’ environmental, and social footprint. This will help students gain the knowledge of a vast
array of data sources such as World Bank Open Dataset, UN SDG Indicators, WRI Aqueduct, FactSet ESG data,
MSCI, WWF Biodiversity Risk Filter and Water Risk Monatizer; and process these data through suitable
methodologies including basic data analytics, statistics, environmental footprint assessment, scenario analysis and
other tools. The course will also present practical examples of the collection and reporting process of corporate data
to comply with CSRD, GRI, SASB, TCFD, CDP and other reporting frameworks, providing insights into the
concepts of data cleanliness, robustness, materiality analysis and stakeholder focus. Students will learn how to apply
this knowledge both for immediate needs of companies to meet the growing investor interest and regulatory
expectations, and to develop sustainability solutions.
- Topics on: Analytics, Data Science, Reporting and Measurement
- Course
The course provides an overview of the opportunities and challenges of transnational financing from public and private
sources that seeks to support mitigation and adaptation investments intended to address climate change. Although there is increased and widespread commitment to taking climate action on the part of corporations, financial institutions, countries and sub-national actors, there remains a paucity of examples where a just transition has been furthered. The conditions engendered by the advent of widespread pandemics have exacerbated global differences in capacity and access to
solutions. Nevertheless, the emergence of new financial mechanisms and global cooperative responses to the pandemic
have revealed potential methods to finance enhancements in mitigation and adaptation in the regions where these are most
lacking. We examine current capital and trade flows and their relationship to flows of embedded carbon, methods of
carbon pricing and the implementation of low-carbon pathways, with an evaluation of decentralized co-benefits that can
advance sustainable development. We combine analysis of carbon accounting and financial structuring to design potential
investments in example decarbonization projects which integrate additionality in mitigation and adaptation, co-benefits
and poverty alleviation.
- Topics on: Finance
- Course
Carbon markets have become a central tool in global efforts to reduce greenhouse gas emissions. This course
explores the economics, institutions, and pricing mechanisms that shape these markets, providing students with a
fundamental description and analysis of emissions trading systems (ETS), carbon taxes, voluntary carbon markets,
internal carbon transfer pricing and emerging financial instruments. Beginning with microeconomic foundations
such as externalities and market-based climate policies, students will analyze the role of international organizations
and regulatory frameworks, including the Paris Agreement, the Kyoto Protocol, and regional policies like the EU
Green Deal, the California carbon market and RGGI. Through real-world case studies, students will evaluate carbon
pricing mechanisms across jurisdictions and industries, gaining the analytical skills necessary to assess policy
effectiveness and market integrity. Designed for graduate students in environmental economics, public policy,
sustainability, and finance, this course is particularly relevant for those pursuing careers in climate policy, carbon
finance, and international development.
This course serves as a critical component of the environmental policy and sustainability curriculum, bridging
economic theory with practical policy implementation. By integrating key concepts from environmental economics,
climate governance, and financial markets, it reinforces students’ understanding of how carbon pricing aligns with
broader sustainability goals. Additionally, the course supports programmatic objectives by equipping students with
the technical expertise and policy fluency needed to navigate and shape carbon markets. Whether students aim to
work in governmental agencies, international organizations, or private-sector sustainability roles, this course
provides the necessary foundation to engage with one of the most dynamic areas of climate policy.
- Topics on: Decarbonization, Economics, Governance
- Course
Existing energy sources and the infrastructures that deliver them to users around the world are undergoing
a period of rapid change. Limits to growth, rapidly fluctuating raw material prices, and the emergence of
new technology options all contribute to heightened risk and opportunity in the energy sector. The
purpose of this course is to establish a core energy skill set for energy students and prepare them for more
advanced energy courses by providing a basic language and toolset for understanding energy issues.
Using theoretical and practical understanding of the process by which energy technologies are developed,
financed, and deployed, this course seeks to highlight the root drivers for change in the energy industry,
the technologies that are emerging, and the factors that will determine success in their commercialization.
Understanding these market dynamics also informs good policy design and implementation to meet a
broad range of social welfare goals.
Upon completing the course, students should not only understand the nature of conventional and
emerging energy generation and delivery, but also the tools for determining potential winners and losers
and the innovative pathways to drive their further deployment.
- Topics on: Economics, Energy, Innovation